Signal Extraction for Non-Stationary Multivariate Time Series with Illustrations for Trend Inflation

Tucker McElroy () and Thomas Trimbur

Journal of Time Series Analysis, 2015, vol. 36, issue 2, 209-227

Abstract: type="main" xml:id="jtsa12102-abs-0001"> This article advances the theory and methodology of signal extraction by developing the optimal treatment of difference stationary multivariate time-series models. Using a flexible time-series structure that includes co-integrated processes, we derive and prove formulas for minimum mean square error estimation of signal vectors in multiple series, from both a finite sample and a bi-infinite sample. As an illustration, we present econometric measures of the trend in total inflation that make optimal use of the signal content in core inflation.

Date: 2015
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Working Paper: Signal extraction for nonstationary multivariate time series with illustrations for trend inflation (2012)
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